Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2

Abstract

We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88-0.92]; P-value = 1.58 × 10(-25)). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08-1.17]; P-value = 7.89 × 10(-09)) and rs13294895 (OR = 1.09 [1.06-1.12]; P-value = 2.97 × 10(-11)). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06-1.18]; P-value = 2.77 × 10(-05)). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis.

Figure 1.

Regional association plots for 9q31.2 fine-mapping SNPs in European and Asian ancestry individuals. (A–D) Individual steps from a forward stepwise regression analysis using data from the Caucasian studies, in which the most strongly associated SNP from a given model is included as a covariate in the subsequent model. Chromosome position is indicated on the x-axis, and –log₁₀ P-value on the y-axis. The models represented are adjusted for study and seven ancestry-informative principal components. Each directly genotyped SNP is represented as a single red diamond and the most significant SNP that attained genome-wide significance from each step of the stepwise regression is indicated by a yellow diamond. (E) Regional association plot for the 9q31.2 fine-mapping SNPs in subjects with Asian ancestry tested using a model adjusted for study and two ancestry-informative principal components.

Figure 2.

Plots of genomic annotations with putative functional significance at the 9q31.2 fine-mapping region. (A) Publically available histone modification, DNase hypersensitivity and transcription factor binding data from MCF7 cells were mapped on to the breast cancer associated regions identified by fine-mapping. For SNPs rs10826625 and rs13294895, the iCHAVs were defined as SNPs having r² ≥ 0.8 with either SNP; for rs676256 it was defined as all SNPs with r² ≥ 0.8 and likelihood ratios >1:100 relative to rs676256. There were no other SNPs in the iCHAVs for rs10816625 and rs13294895. The rs676256 iCHAV comprised 28 SNPs. SNPs whose identifiers are shown in red type were of putative functional significance (see Materials and Methods). Where the lead SNP was not deemed to be of putative functional significance, it is indicated in green, as is the index 9q31.2 SNP, rs865686. (B) Regional binding profiles for ER-α in MCF7 cells shown plotted across the fine-mapping region using data from (31). The locations of the lead SNPs are indicated with yellow diamonds. (C) Regional binding profiles for FOXA1 in MCF7 cells shown plotted across the fine-mapping region using data from (31). The locations of the lead SNPs are indicated with yellow diamonds.

Figure 3.

Chromatin conformation capture and reporter gene analysis of SNPs rs10816625 and rs13294895. (A) Chromatin interaction data from HindIII 3C libraries generated using MCF7 cells that indicates interactions between a fragment containing rs10816625 and rs13294895 (dashed line) and fragments surrounding KLF4. Results from three replicate libraries are plotted; each quantitative PCR reaction was performed in triplicate. Error bars represent standard mean errors. (B) Chromatin interaction data from HindIII 3C libraries generated using SUM44 cells. (C) Dual luciferase assays for reporter constructs containing the common alleles of both rs10816625 and rs13294895 (pGL4minP-AB), risk allele of rs10816625 (pGL4minP-aB), risk allele of rs13294895 (pGL4minP-Ab) and risk alleles of both SNPs (pGL4minP-ab) transiently transfected into MCF7 cells. Ratios were normalised to a minimal promoter construct (pGL4minP). Each transfection was repeated five times and constructs were generated in both forward and reverse orientations. (D) Dual luciferase assays for reporter constructs containing the common alleles of both rs10816625 and rs13294895 (pGL4minP-AB), risk allele of rs10816625 (pGL4minP-aB), risk allele of rs13294895 (pGL4minP-Ab) and risk alleles of both SNPs (pGL4minP-ab) transiently transfected into T47D cells.